Br J Cancer. 2015 Feb 26. doi: 10.1038/bjc.2014.636. [Epub ahead of print]

DNA hypermethylation analysis in sputum for the diagnosis of lung cancer: training validation set approach.

Hubers AJ1, Heideman DA1, Burgers SA2, Herder GJ3, Sterk PJ4, Rhodius RJ4, Smit HJ5, Krouwels F6, Welling A7, Witte BI8, Duin S1,Koning R1, Comans EF9, Steenbergen RD1, Postmus PE10, Meijer GA1, Snijders PJ1, Smit EF10, Thunnissen E1.

Author information

• 1Department of Pathology, VU University Medical Center, De Boelelaan 1117, Amsterdam 1081 HV, The Netherlands.
• 2Department of Thoracic Oncology, NKI-Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands.
• 3Department of Pulmonary Diseases, Sint Antonius Hospital, Nieuwegein, The Netherlands.
• 4Department of Pulmonary Diseases, Academic Medical Center, Amsterdam, The Netherlands.
• 5Department of Pulmonary Diseases, Sint Lucas Andreas Hospital, Amsterdam, The Netherlands.
• 6Department of Pulmonary Diseases, Spaarne Hospital, Hoofddorp, The Netherlands.
• 7Department of Pulmonary Diseases, Medisch Centrum Alkmaar, Alkmaar, The Netherlands.
• 8Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands.
• 9Department of Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands.
• 10Department of Pulmonary Diseases, VU University Medical Center, Amsterdam, The Netherlands.

Abstract

Background:Lung cancer has the highest mortality of all cancers. The aim of this study was to examine DNA hypermethylation in sputum and validate its diagnostic accuracy for lung cancer.Methods:DNA hypermethylation of RASSF1A, APC, cytoglobin, 3OST2, PRDM14, FAM19A4 and PHACTR3 was analysed in sputum samples from symptomatic lung cancer patients and controls (learning set: 73 cases, 86 controls; validation set: 159 cases, 154 controls) by quantitative methylation-specific PCR. Three statistical models were used: (i) cutoff based on Youden's J index, (ii) cutoff based on fixed specificity per marker of 96% and (iii) risk classification of post-test probabilities.Results:In the learning set, approach (i) showed that RASSF1A was best able to distinguish cases from controls (sensitivity 42.5%, specificity 96.5%). RASSF1A, 3OST2 and PRDM14 combined demonstrated a sensitivity of 82.2% with a specificity of 66.3%. Approach (ii) yielded a combination rule of RASSF1A, 3OST2 and PHACTR3 (sensitivity 67.1%, specificity 89.5%). The risk model (approach iii) distributed the cases over all risk categories. All methods displayed similar and consistent results in the validation set.Conclusions:Our findings underscore the impact of DNA methylation markers in symptomatic lung cancerdiagnosis. RASSF1A is validated as diagnostic marker in lung cancer.